Robust Nonlinear Tracking Control with Exponential Convergence Using Contraction Metrics and Disturbance Estimation
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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Author to whom correspondence should be addressed.
Academic Editor: Baochang Zhang
Sensors 2022, 22(13), 4743; https://doi.org/10.3390/s22134743
Received: 9 May 2022
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Revised: 9 June 2022
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Accepted: 20 June 2022
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Published: 23 June 2022
(This article belongs to the Special Issue Motion Optimization and Control of Single and Multiple Autonomous Aerial, Land, and Marine Robots)
This paper presents a tracking controller for nonlinear systems with matched uncertainties based on contraction metrics and disturbance estimation that provides exponential convergence guarantees. Within the proposed approach, a disturbance estimator is proposed to estimate the pointwise value of the uncertainties, with a pre-computable estimation error bounds (EEB). The estimated disturbance and the EEB are then incorporated in a robust Riemannian energy condition to compute the control law that guarantees exponential convergence of actual state trajectories to desired ones. Simulation results on aircraft and planar quadrotor systems demonstrate the efficacy of the proposed controller, which yields better tracking performance than existing controllers for both systems.
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Keywords:
robust control; nonlinear control; uncertain systems; disturbance estimation; robot safety
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MDPI and ACS Style
Zhao, P.; Guo, Z.; Hovakimyan, N. Robust Nonlinear Tracking Control with Exponential Convergence Using Contraction Metrics and Disturbance Estimation. Sensors 2022, 22, 4743. https://doi.org/10.3390/s22134743
AMA Style
Zhao P, Guo Z, Hovakimyan N. Robust Nonlinear Tracking Control with Exponential Convergence Using Contraction Metrics and Disturbance Estimation. Sensors. 2022; 22(13):4743. https://doi.org/10.3390/s22134743
Chicago/Turabian StyleZhao, Pan, Ziyao Guo, and Naira Hovakimyan. 2022. "Robust Nonlinear Tracking Control with Exponential Convergence Using Contraction Metrics and Disturbance Estimation" Sensors 22, no. 13: 4743. https://doi.org/10.3390/s22134743
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